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The AI security question leaders should be asking instead

Gremlin security officer Frederic Bull argues AI has eroded the attacker-defender skill asymmetry while least-privilege controls remain essential for securing AI agents.

In a Help Net Security interview, Gremlin Security Officer Frederic Bull says AI has narrowed the expertise gap between attackers and defenders, enabling faster exploit discovery even by less-skilled actors. His team processed roughly nine times more vulnerabilities in the past year with unchanged staffing using LLM-based tooling, cutting time-to-remediate by about 5%. He argues least privilege, session-based RBAC via OIDC/OBO, and human-in-the-loop oversight remain the bedrock defenses for AI agents, and that hiring should favor engineers able to catch confidently wrong AI output.

Help Net Security · 2h agoIndustry

When Agents Look Like Beacons: NIDS Evasion by Model Context Protocol Traffic

Research shows Model Context Protocol agent traffic structurally resembles C2 beaconing and evades Suricata signatures and RITA behavioral scoring in testbeds.

An arXiv study demonstrates that Model Context Protocol (MCP) JSON-RPC traffic over Streamable HTTP mimics the polling patterns of C2 frameworks like Cobalt Strike and is not flagged as anomalous by standard enterprise defenses. In a Docker testbed with eleven traffic profiles across three TLS conditions, Suricata with the Emerging Threats Open ruleset produced near-zero alerts and RITA assigned a consistent 0.0 beacon score, regardless of jitter or TLS inspection. The authors propose an agent-native network indication standard using Agent-Native ALPN and out-of-band headers.

arXiv cs.CR · 14h agoResearch

NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut

NVIDIA's Vera Rubin NVL72 debuts in MLPerf Inference v6.1 with up to 3.7x higher throughput than GB300 NVL72 and 99% scaling efficiency at 288 GPUs.

In its first MLPerf Inference preview submission, NVIDIA's Vera Rubin NVL72 achieved up to 3.7x higher throughput than GB300 NVL72 on Qwen3-VL and 2.5x on DeepSeek-R1. A 288-GPU GB300 NVL72 submission across four racks reached 99% scaling efficiency on the DeepSeek-R1 offline benchmark. Software optimizations delivered up to 1.6x gains over v6.0, leveraging TensorRT-LLM, vLLM, Dynamo, disaggregated serving, and NVFP4 precision.

NVIDIA Blog · 16h agoAI industry 2 sources

Securing the unpatchable in an age of AI-driven vulnerabilities

Cisco Talos argues AI-driven vulnerability discovery leaves unpatchable OT systems exposed, recommending virtual patching via NGFW/IPS and micro-segmentation.

AI-assisted code analysis is uncovering vulnerabilities faster than organizations can patch, leaving certified or end-of-life OT systems with unmitigated known flaws. Talos recommends virtual patching with next-generation firewalls and IPS, micro-segmentation using VLANs and ACLs, and building visibility-based inventories of legacy systems. The article cites WannaCry's impact on the NHS and 2023 exploitation of end-of-life software in government systems, and warns that air gaps and data diodes are routinely circumvented by operational shortcuts.

Cisco Talos · 21h agoResearch